SOLAR ENERGY TIME SERIES ANALYSIS VIA MARKOV CHAINS

Resumen

Brazil, given a global scenario of concern with climate change, has been increasing the use of renewable energy, especially solar energy in the last years. With the growth in its participation, the characteristics of solar energy, such as intermittence and random fluctuations, have been affecting the operation planning of the Brazilian Electricity System (BES). Such factors can be studied with time series modeling, helping the planning of power plants and BES. In order to contribute to the factor analysis, the objective of this research is to analyze the characteristics of photovoltaic energy generation in the meteorological seasons of the year in two regions of Brazil with different solar incidences. For this, a methodology based on Markov Chain concepts is applied. The work stands out for the subdivision of the time series between the climatic seasons, for the use of data not yet studied and for the presentation of the methodology and results in detail. The objective of the research was successfully achieved, making evident the differences between the solar energy generation models between the meteorological seasons and the two regions studied.